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Abstract Background Following a stroke, brain activation reorganisation, movement compensatory strategies, motor performance and their evolution through rehabilitation are matters of importance for clinicians. Two non-invasive neuroimaging methods allow for recording task-related brain activation: functional near-infrared spectroscopy (fNIRS) and electroencephalography (fEEG), respectively based on hemodynamic response and neuronal electrical activity. Their simultaneous measurement during movements could allow a better spatiotemporal mapping of brain activation, and when associated to kinematic parameters could unveil underlying mechanisms of functional upper limb (UL) recovery. This study aims to depict the motor cortical activity patterns using combined fNIRS-fEEG and their relationship to motor performance and strategies during UL functional tasks in chronic post-stroke patients. Methods Twenty-one healthy old adults and 21 chronic post-stroke patients were recruited and completed two standardised functional tasks of the UL: a paced-reaching task where they had to reach a target in front of them and a circular steering task where they had to displace a target using a hand-held stylus, as fast as possible inside a circular track projected on a computer screen. The activity of the bilateral motor cortices and motor performance were recorded simultaneously utilizing a fNIRS-fEEG and kinematics platform. Results and conclusions Kinematic analysis revealed that post-stroke patients performed worse in the circular steering task and used more trunk compensation in both tasks. Brain analysis of bilateral motor cortices revealed that stroke individuals over-activated during the paretic UL reaching task, which was associated with more trunk usage and a higher level of impairment (clinical scores). This work opens up avenues for using such combined methods to better track and understand brain-movement evolution through stroke rehabilitation.

The climate of the Tibetan Plateau (TP) has experienced substantial changes in recent decades as a result of the location's susceptibility to global climate change. The changes observed across the TP are closely associated with regional land–atmosphere interactions. Current models and satellites struggle to accurately depict the interactions; therefore, critical field observations on land–atmosphere interactions outlined here provide necessary independent validation data and fine-scale process insights for constraining reanalysis products, remote sensing retrievals, and land surface model parameterizations. Scientific data sharing is crucial for the TP since in situ observations are rarely available under these harsh conditions. However, field observations are currently dispersed among individuals or groups and have not yet been integrated for comprehensive analysis. This has prevented a better understanding of the interactions, the unprecedented changes they generate, and the substantial ecological and environmental consequences they bring about. In this study, we collaborated with different agencies and organizations to present a comprehensive dataset for hourly measurements of surface energy balance components, soil hydrothermal properties, and near-surface micrometeorological conditions spanning up to 17 years (2005–2021). This dataset, derived from 12 field stations covering a variety of typical TP landscapes, provides the most extensive in situ observation data available for studying land–atmosphere interactions on the TP to date in terms of both spatial coverage and duration. Three categories of observations are provided in this dataset: meteorological gradient data (met), soil hydrothermal data (soil), and turbulent flux data (flux). To assure data quality, a set of rigorous data-processing and quality control procedures are implemented for all observation elements (e.g., wind speed and direction at different height) in this dataset. The operational workflow and procedures are individually tailored to the varied types of elements at each station, including automated error screening, manual inspection, diagnostic checking, adjustments, and quality flagging. The hourly raw data series; the quality-assured data; and supplementary information, including data integrity and the percentage of correct data on a monthly scale, are provided via the National Tibetan Plateau Data Center (https://doi.org/10.11888/Atmos.tpdc.300977, Ma et al., 2023a). With the greatest number of stations covered, the fullest collection of meteorological elements, and the longest duration of observations and recordings to date, this dataset is the most extensive hourly land–atmosphere interaction observation dataset for the TP. It will serve as the benchmark for evaluating and refining land surface models, reanalysis products, and remote sensing retrievals, as well as for characterizing fine-scale land–atmosphere interaction processes of the TP and underlying influence mechanisms.

Accurate, detailed, and up-to-date information on cropland extent is crucial for provisioning food security and environmental sustainability. However, because of the complexity of agricultural landscapes and lack of sufficient training samples, it remains challenging to monitor cropland dynamics at high spatial and temporal resolutions across large geographical extents, especially for regions where agricultural land use is changing dramatically. Here we developed a cost-effective annual cropland mapping framework that integrated time-series Landsat satellite imagery, automated training sample generation, as well as machine learning and change detection techniques. We implemented the proposed scheme to a cloud computing platform of Google Earth Engine and generated a novel dataset of China's annual cropland at a 30 m spatial resolution (namely CACD). Results demonstrated that our approach was capable of tracking dynamic cropland changes in different agricultural zones. The pixel-wise F1 scores for annual maps and change maps of CACD were 0.79 ± 0.02 and 0.81, respectively. Further cross-product comparisons, including accuracy assessment, correlations with statistics, and spatial details, highlighted the precision and robustness of CACD compared with other datasets. According to our estimation, from 1986 to 2021, China's total cropland area expanded by 30 300 km2 (1.79 %), which underwent an increase before 2002 but a general decline between 2002 and 2015, and a slight recovery afterward. Cropland expansion was concentrated in the northwest while the eastern, central, and southern regions experienced substantial cropland loss. In addition, we observed 419 342 km2 (17.57 %) of croplands that were abandoned at least once during the study period. The consistent, high-resolution data of CACD can support progress toward sustainable agricultural use and food production in various research applications. The full archive of CACD is freely available at https://doi.org/10.5281/zenodo.7936885 (Tu et al., 2023a).

The interactions between the terrestrial biosphere, atmospheric chemistry, and climate involve complex feedbacks that have traditionally been modeled separately. We present a new framework that couples the Yale Interactive terrestrial Biosphere (YIBs) model, a dynamic plant-chemistry model, with the RegCM-Chem model. RegCM-Chem–YIBs integrates meteorological variables and atmospheric chemical composition from RegCM-Chem with land surface parameters from YIBs. The terrestrial carbon flux calculated by YIBs is fed back into RegCM-Chem interactively, thereby representing the interactions between fine particulate matter (PM2.5), ozone (O3), and carbon dioxide (CO2). For testing purposes, we carry out a 1-year simulation (2016) at a 30 km horizontal resolution over East Asia with RegCM-Chem–YIBs. The model accurately captures the spatio-temporal distribution of climate, chemical composition, and ecological parameters. In particular, the estimated O3 and PM2.5 are consistent with ground observations, with correlation coefficients (R) of 0.74 and 0.65, respectively. The simulated CO2 concentration is consistent with observations from six sites (R ranged from 0.89 to 0.97) and exhibits a similar spatial pattern when compared with carbon assimilation products. RegCM-Chem–YIBs produces reasonably good gross primary productivity (GPP) and net primary productivity (NPP), showing seasonal and spatial distributions consistent with satellite observations, and mean biases (MBs) of 0.13 and 0.05 kg C m−2 yr−1. This study illustrates that RegCM-Chem–YIBs is a valuable tool to investigate coupled interactions between the terrestrial carbon cycle, atmospheric chemistry, and climate change at a higher resolution on a regional scale.

Abstract Using high‐resolution data from the Magnetospheric Multiscale mission, an electron‐only reconnection current sheet is found between two successive dipolarization fronts (DFs). The electron‐only reconnection occurs between the northward component of the magnetic field of the flux pileup region (FPR) of the first DF (DF1) and the southward component of the magnetic dip of the second DF (DF2). The faster DF2 compresses the FPR of DF1, which constitutes an anti‐parallel topology and reduces the thickness of the current sheet. Further analysis shows that the current sheet is unstable to the electron tearing instability, which may power the onset of the reconnection. Our results suggest that these two DFs may merge into one by the reconnection, which sheds light on the evolution of DFs during their earthward propagation.

Abstract Magnetic reconnection is the physical process that converts the energy from the fields to the plasmas in space, astrophysical and laboratory plasmas. The Reconnection front (RF) is the structure generated in the reconnection outflow region and participates in the energy release budget. Here, we first report a novel crater structure of magnetic field behind the RF, which is well supported by both the in‐situ observations from the Magnetospheric Multiscale mission and kinetic particle‐in‐cell simulations. The theoretical explanations from the simulations suggests that the formation of the crater structure is possibly due to that high‐speed outflow electron jet from inner electron diffusion region constantly strikes the RF. From another perspective, the crater structure is the continuous impact of the electron jet. Our results can establish a new understanding of the RF and energy conversion during magnetic reconnection.

Abstract Electron vortices are usually embedded within different magnetic structures in space plasmas. The effects, including the nonideal electric field, energy dissipation and magnetic field, of electron vortices on these magnetic structures are still unclear. Utilizing the unprecedented high‐resolution data from the Magnetospheric Multiscale mission in the terrestrial magnetosheath, we statistically investigate these effects on magnetic structures. Both nonideal electric fields and energy dissipation have no obvious correlations with the scales of electron vortices. However, compared to the scales, stronger correlations are found between the vorticities of electron vortices and nonideal electric fields, and energy dissipation, respectively. Most of electron vortices have positive contributions to magnetic fields of magnetic structures, such as strengthening the decrease (or increase) of Bt for current sheets and magnetic holes (or flux ropes and magnetic peaks). Our results reveal that the electron vortices play an important role in the evolution of magnetic structures.

Abstract Dipolarization fronts (DFs) are widely believed to host energy conversion processes. However, which mechanism is responsible for the energy conversion is still obscure. Using data from the Magnetospheric Multiscale mission, a current sheet is observed at a DF. This current sheet is caused by interchange instability bending the edge of the DF. Inside the current sheet, Hall electromagnetic field, super Alfvénic electron jets, demagnetization of ions and electrons, strong energy conversion, and steady ion flow and temperature are observed, indicating an electron‐only reconnection at the DF. The duskward plasma flow, which may be deflected by the DF, compresses the bent edges of the DF. As a result, the width of the current sheet between two adjacent bent edges of the DF reduces, and then reconnection begins. Our observations give direct evidence that magnetic reconnection results in energy conversion at a DF.

Dopaminergic neurons are the predominant brain cells affected in Parkinson’s disease. With the limited availability of live human brain dopaminergic neurons to study pathological mechanisms of Parkinson’s disease, dopaminergic neurons have been generated from human-skin-cell-derived induced pluripotent stem cells. Originally, induced pluripotent stem-cell-derived dopaminergic neurons were generated using small molecules. These neurons took more than two months to mature. However, the transcription-factor-mediated differentiation of induced pluripotent stem cells has revealed quicker and cheaper methods to generate dopaminergic neurons. In this study, we compared and contrasted three protocols to generate induced pluripotent stem-cell-derived dopaminergic neurons using transcription-factor-mediated directed differentiation. We deviated from the established protocols using lentivirus transduction to stably integrate different transcription factors into the AAVS1 safe harbour locus of induced pluripotent stem cells. We used different media compositions to generate more than 90% of neurons in the culture, out of which more than 85% of the neurons were dopaminergic neurons within three weeks. Therefore, from our comparative study, we reveal that a combination of transcription factors along with small molecule treatment may be required to generate a pure population of human dopaminergic neurons.

Statistical methods, particularly machine learning models, have gained significant popularity in air quality predictions. These prediction models are commonly trained using the historical measurement datasets independently collected at the environmental monitoring stations and their operational forecasts in advance using inputs of the real-time ambient pollutant observations. Therefore, these high-quality machine learning models only provide site-available predictions and cannot solely be used as the operational forecast. In contrast, deterministic chemical transport models (CTMs), which simulate the full life cycles of air pollutants, provide predictions that are continuous in the 3D field. Despite their benefits, CTM predictions are typically biased, particularly on a fine scale, owing to the complex error sources due to the emission, transport, and removal of pollutants. In this study, we proposed a fusion of site-available machine learning prediction, which is from our regional feature selection-based machine learning model (RFSML v1.0), and a CTM prediction. Compared to the normal pure machine learning model, the fusion system provides a gridded prediction with relatively high accuracy. The prediction fusion was conducted using the Bayesian-theory-based ensemble Kalman filter (EnKF). Background error covariance was an essential part in the assimilation process. Ensemble CTM predictions driven by the perturbed emission inventories were initially used for representing their spatial covariance statistics, which could resolve the main part of the CTM error. In addition, a covariance inflation algorithm was designed to amplify the ensemble perturbations to account for other model errors next to the uncertainty in emission inputs. Model evaluation tests were conducted based on independent measurements. Our EnKF-based prediction fusion presented superior performance compared to the pure CTM. Moreover, covariance inflation further enhanced the fused prediction, particularly in cases of severe underestimation.

Exploring the snow depth on Mount Everest, one of the most inaccessible places on our planet, has long been a topic of interest. Previously reported snow depths have been inconsistent and have large uncertainties. Here, we report the ground-penetrating radar survey of snow depth along the north slope of Mount Everest in May 2022. Our radar measurements display a gradual increasing transition of snow depth along the north slope, and the mean depth estimates at the summit are 9.5±1.2 m. This updated snow depth on Mount Everest is much deeper than previously reported values (0.9–3.5 m).

The process of digital restoration of lost cultural heritage often takes a lot of effort and it is difficult to judge the accuracy of the restoration. In this paper, we propose a set of basic methods and processes for digital restoration based on the lost heritage by mining materials and information, and can trace the evidence based on the restoration results. Taking the restoration of the South Gate of the Shangjing Palace in the Liao Dynasty as an example, this paper introduces the methods and processes of establishing a database of restoration materials and identifying relevant information, restoration design steps and accuracy assessment in the process of digital restoration, and finally realizing the digital presentation of the lost heritage. It is hoped that this paper can provide problem-solving ideas and methods for workers in the field of digital restoration of vanished heritage.

Introduction: Neurosurgery is considered a technically demanding specialty; nonetheless, it also requires non-technical skills (NTSs) to reach mastery. Research question: This study seeks to understand how important NTSs are perceived by neurosurgeons across diverse roles and socio-economic backgrounds. The objective is to identify key NTSs and explore their role in surgical precision, teamwork, and collaboration. Material and method: An international survey involving 372 neurosurgeons from various socio-economic and cultural contexts was conducted. The extensive sample and inclusive methodology provide a comprehensive perspective on the perceived importance of NTSs in neurosurgery. Results: The survey results highlight the universal significance of NTSs among neurosurgeons. Attention to detail, humility, and self-awareness are considered essential for surgical precision, effective teamwork, and collaboration. The findings underscore the necessity for integrated training programs that combine NTSs with technical skills. Discussion and conclusion: The study emphasizes the importance of effective training methods such as simulations, mentorship, and role-playing in equipping neurosurgeons to navigate the complexities of their profession. Future research should focus on optimizing teaching methods for NTSs, comparing traditional courses, online modules, and hybrid training programs. Addressing the global disparity in neurosurgical care, particularly in low- and middle-income countries, is crucial for improving patient outcomes worldwide.

Cancer cells evolve to be refractory to the intrinsic programmed cell death mechanisms, which ensure cellular tissue homeostasis in physiological conditions. Chemotherapy using cytotoxic drugs seeks to eliminate cancer cells but spare non-cancerous host cells by exploring a likely subtle difference between malignant and benign cells. Presumably, chemotherapy agents achieve efficacy by triggering programmed cell death machineries in cancer cells. Currently, many major solid tumors are treated with chemotherapy composed of a combination of platinum agents and taxanes. Platinum agents, largely cis-platin, carboplatin, and oxaliplatin, are DNA damaging agents that covalently form DNA addicts, triggering DNA repair response pathways. Taxanes, including paclitaxel, docetaxel, and cabazitaxel, are microtubule stabilizing drugs which are often very effective in purging cancer cells in clinical settings. Generally, it is thought that the stabilization of microtubules by taxanes leads to mitotic arrest, mitotic catastrophe, and the triggering of apoptotic programmed cell death. However, the precise mechanism(s) of how mitotic arrest and catastrophe activate the caspase pathway has not been established. Here, we briefly review literature on the involvement of potential cell death mechanisms in cancer therapy. These include the classical caspase-mediated apoptotic programmed cell death, necroptosis mediated by MLKL, and pore forming mechanisms in immune cells, etc. In particular, we discuss a newly recognized mechanism of cell death in taxane-treatment of cancer cells that involves micronucleation and the irreversible rupture of the nuclear membrane. Since cancer cells are commonly retarded in responding to programmed cell death signaling, stabilized microtubule bundle-induced micronucleation and nuclear membrane rupture, rather than triggering apoptosis, may be a key mechanism accounting for the success of taxanes as anti-cancer agents.

The hydrodynamics characteristics in a tank with an up-down reciprocating disc agitator were numerically investigated using computational fluid dynamics (CFD) simulations. A dynamic mesh technique along with a user-defined function (UDF) was used to solve the reciprocating movement of the disc agitator in the tank. The dynamic flow field and averaged values of some important parameters were obtained. The verification of the simulation was completed by comparing its results with experimental data in the literature. It is found that the flow pattern in the tank with a reciprocating agitator is characterized by two dynamic vortices, which are above and below the disc, respectively. Flow field, force acting on the disc and power requirement change periodically in the tank. The increase of frequency, amplitude and disc diameter leads to the increase of the averaged velocity in the tank as a whole. Nevertheless, the uniformity of velocity distribution is slightly improved, worsened and greatly improved respectively under the above operating conditions. The averaged values of the force acting on the disc and power consumption are in the second and the third power relations with the reciprocating frequency and amplitude, respectively. The ratio of fluid averaged velocity in one cycle to averaged disc speed, and Newton number are hardly affected by reciprocating frequency and amplitude, while they increase with the enlarged size of the disc agitator.

In this study, we investigate the spatiotemporal dynamics of the neural oscillations by analyzing the electric potential that arises from neural activity. We identify two types of dynamics based on the frequency and phase of oscillations: standing waves or as out-of-phase and modulated waves, which represent a combination of standing and moving waves. To characterize these dynamics, we use optical flow patterns such as sources, sinks, spirals and saddles. We compare analytical and numerical solutions with real EEG data acquired during a picture-naming task. Analytical approximation of standing waves helps us to establish some properties of pattern location and number. Specifically, sources and sinks are mainly located in the same location, while saddles are positioned between them. The number of saddles correlates with the sum of all the other patterns. These properties are confirmed in both the simulated and real EEG data. In particular, source and sink clusters in the EEG data overlap with each other with median percentages around 60%, and hence have high spatial correlation, while source/sink clusters overlap with saddle clusters in less than 1%, and have different locations. Our statistical analysis showed that saddles account for about 45% of all patterns, while the remaining patterns are present in similar proportions.

Abstract Magnetic reconnection is a fundamental physical process of rapidly converting magnetic energy into particles. The electron diffusion region (EDR) is the crucial region during magnetic reconnection. The outer EDR, which also plays a crucial role in magnetic reconnection, is responsible for energy conversion. In the outer EDR, the electrons are decelerated and return the energy to the magnetic field on the pileup region behind the reconnection front. In the present study, we used the fully kinetic particle‐in‐cell simulation and revealed that part of decelerated electrons in the outer EDR could even move back to the inner EDR. This phenomenon is caused by the dominant contribution from the magnetic tension force, and it suggests a magnetic Marangoni effect in space plasma, similar to the Marangoni effect in fluids. Our results potentially propose a brand‐new physical process and a novel mechanism in the EDR during magnetic reconnection.

Abstract In Saturn's magnetosphere, the plasma temperature increases with radial distance, requiring a heating mechanism to counteract the adiabatic cooling effect of expanding plasma. To explore potential heating source, we perform a statistical study about intermittent structures and intermittent heating in Saturn's magnetosphere based on the observations from the Cassini spacecraft. Partial Variance of Increments (PVI) technique is used to measure the intermittency of magnetic field and identify the intermittent structures. It is found that the electron temperature has a rising trend as the increase of magnetic field intermittency, implying the occurrence of electron heating in the intermittent structures. Additionally, the turbulence heating rate also exhibits an increasing trend as the increase of probability density of intermittent structures. Our results evidence the effect of intermittent heating in the Saturn's magnetosphere, and suggest that intermittent structures with high magnetic field intermittency play an important role in turbulence heating.

In this study, we developed an approach that integrated multiple patterns of timescale for box modeling (MCMv3.3.1) to better understand the O3–precursor relationship at multiple sites and through continuous observations. A 5-month field campaign was conducted in the summer of 2019 to investigate the ozone formation chemistry at three sites in a major prefecture-level city (Zibo) in Shandong Province of northern China. It was found that the relative incremental reactivity (RIR) of major precursor groups (e.g., anthropogenic volatile organic compounds (AVOCs), NOx) was overall consistent in terms of timescales changed from wider to narrower (four patterns: 5-month, monthly, weekly, and daily) at each site, though the magnitudes of RIR varied at different sites. The time series of the photochemical regime (using RIRNOx / RIRAVOC as an indicator) in weekly or daily patterns further showed a synchronous temporal trend among the three sites, while the magnitude of RIRNOx / RIRAVOC was site-to-site dependent. The derived RIR ranking (top 10) of individual AVOC species showed consistency between three patterns (i.e., 5-month, monthly, and weekly). It was further found that the campaign-averaging photochemical regimes showed overall consistency in the sign but non-negligible variability among the four patterns of timescale, which was mainly due to the embedded uncertainty in the model input dataset when averaging individual daily patterns into different timescales. This implies that utilizing narrower timescales (i.e., daily pattern) is useful for deriving reliable and robust O3–precursor relationships. Our results highlight the importance of quantifying the impact of different timescales to constrain the photochemical regime, which can formulate more accurate policy-relevant guidance for O3 pollution control.

Secondary organic aerosols (SOAs) are important components of fine particulates in the atmosphere. However, the sources of SOA precursor and atmospheric processes affecting SOAs are poorly understood. This limits our abilities to improve air quality and model aerosol-mediated climate forcing. Here, we use novel compound-specific dual-carbon isotope fingerprints (Δ14C and δ13C) for individual SOA tracer molecules (i.e., oxalic acid) to investigate the fates of SOAs in the atmosphere at five emission hotspots in China. Coal combustion and vehicle exhaust accounted for ∼ 55 % of the sources of carbon in oxalic acid in Beijing and Shanghai, but biomass burning and biogenic emissions accounted for ∼ 70 % of the sources of carbon in oxalic acid in Chengdu, Guangzhou, and Wuhan during the sampling period. The dual-carbon isotope signatures of oxalic acid and bulk organic carbon pools (e.g., water-soluble organic carbon) were compared to investigate the fates of SOAs in the atmosphere. Photochemical aging and aqueous-phase chemical processes dominate the formation of oxalic acid in summer and in winter, respectively. The results indicated that SOA carbon sources and chemical processes producing SOAs vary spatially and seasonally, and these variations need to be included in Chinese climate projection models and air quality management practices.

Abstract The Kolmogorov scaling in the inertial range of scales is a distinct characteristic of fully developed turbulence, and studying it offers valuable insights into the evolution of turbulence. In this work, we perform a statistical survey of the power spectra with the Kolmogorov scaling in Saturn's magnetosphere using Cassini measurements. Two cases study show that both magnetic‐field and electron density spectra exhibit f −5/3 at the MHD scales. The statistical analysis reveals a wide‐ranging and abundant presence of Kolmogorov spectra throughout magnetosphere, observed across all local times. Interestingly, the occurrence rate of these Kolmogorov‐like events within Saturn's magnetosphere surpasses that observed in the planetary magnetosheath. The measurements of magnetic compressibility for the Kolmogorov‐like events show the dominance of incompressible Alfvénic turbulence (44.64%) with respect to magnetosonic‐like one (6.94%). In addition, the source and evolution of the turbulent fluctuations are further discussed.

Abstract Gravitational‐wave high‐energy Electromagnetic Counterpart All‐sky Monitor (GECAM) is a space‐borne instrument dedicated to monitoring high‐energy transients, including Terrestrial Gamma‐ray Flashes (TGFs) and Terrestrial Electron Beams (TEBs). We implemented a TGF/TEB search algorithm for GECAM, with which 147 bright TGFs, 2 typical TEBs and 2 special TEB‐like events are identified during an effective observation time of ∼9 months. We show that, with gamma‐ray and charged particle detectors, GECAM can effectively identify and distinguish TGFs and TEBs, and measure their temporal and spectral properties in detail. A very high TGF‐lightning association rate of ∼80% is obtained between GECAM and GLD360 in east Asia region.

Based on high-resolution measurements from the Magnetospheric Multiscale mission from 2015 May to 2018 June, we statistically investigate the properties of small-scale field-aligned currents (SFACs) in the magnetopause boundary layer. A total of 2235 SFACs are successfully identified. The durations of SFACs mainly fall between 0.2 and 0.3 s. Over 90% of SFACs have a width of less than 1 ion inertia length and are primarily distributed from 5 to 25 electron inertia lengths, implying that the SFACs belong to the kinetic-scale current layer. The main carriers of SFACs are electrons, and over 70% of SFACs exhibit net energy dissipation (i.e., J · E ′ > 0) with the majority of energy dissipation taking place in the parallel direction. SFACs are widely distributed spatially, and the occurrence rate of SFACs is higher in the boundary layer closer to the magnetosphere. Additionally, less than half of the total SFACs are identified in well-known structures, including the magnetic reconnection region, flux transfer event, Kelvin–Helmholtz vortex, and exhaust region, and 54% of the SFACs are in the “others” unknown structures. These results improve our comprehension of the current system at the magnetopause and the roles of SFACs in the coupling between the solar wind and magnetosphere.

Glaciers are recognized as a biome dominated by microorganisms and a reservoir of organic carbon and nutrients. Global warming remarkably increases glacier melting rate and runoff volume, which have significant impacts on the carbon and nitrogen cycles in downstream ecosystems. The Tibetan Plateau (TP), dubbed “the water tower of Asia”, owns the largest mountain glacial area at mid- and low-latitudes. However, limited data on the microbial abundance, organic carbon, and nitrogen in TP glaciers are available in the literature, which severely hinders our understanding of the regional carbon and nitrogen cycles. This work presents a new dataset on microbial abundance, dissolved organic carbon (DOC), and total nitrogen (TN) for TP glaciers. In this dataset, there are 5409 records from 12 glaciers for microbial abundance in ice cores and snow pits, and 2532 records from 38 glaciers for DOC and TN in the ice core, snow pit, surface ice, surface snow, and proglacial runoff. These glaciers are located across diverse geographic and climatic regions, where the multiyear average air temperature ranges from −13.4 to 2.9 ∘C and the multiyear average precipitation ranges from 76.9 to 927.8 mm. This makes the constructed dataset qualified for large-scale studies across the TP. To the best of our knowledge, this is the first dataset of microbial abundance and TN in TP glaciers and also the first dataset of DOC in ice cores of the TP. This new dataset provides important information for studies on carbon and nitrogen cycles in glacial ecosystems, and is especially valuable for the assessment of potential impacts of glacier retreat on downstream ecosystems under global warming. The dataset is available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.271841; Liu, 2021).

In urban areas, the None-Line-Of-Sight (NLOS) and Multipath (MP) signals are the major issues degrading the GNSS position accuracy. Signal reception type should be identified before correcting the NLOS or MP induced errors. Signal features, i.e., signal strength, change rate of received signal strength, difference between delta pseudo-range and pseudo-range rate, have been explored in signal reception type classification. In this letter, with the aim to improve the signal classification accuracy, we propose a new GNSS NLOS/MP/LOS signals classification method using the correlator-level measurements. Firstly, vector tracking (VT) is employed to generate correlator-level measurements; secondly, a deep learning method, Convolutional Neural Network (CNN), is employed to automatically extract the features and identify the signal reception type, correlators’ outputs calculated at different code phases are employed as the inputs of the CNN. Field test is carried out for assessing the performance of the proposed method, and the CNN method obtains state-of-art performance compared with the K-nearest Neighbors Algorithm (kNN) and Support Vector Machine (SVM) methods.

Springback is an inevitable problem in the local bending process of hull plates, which leads to low processing efficiency and affects the assembly accuracy. Therefore, the prediction of the springback effect, as a result of the local bending of hull plates, bears great significance. This paper proposes a springback prediction model based on a backpropagation neural network (BPNN), considering geometric and process parameters. Genetic algorithm (GA) and improved particle swarm optimization (PSO) algorithms are used to improve the global search capability of BPNN, which tends to fall into local optimal solutions, in order to find the global optimal solution. The result shows that the proposed springback prediction model, based on the BPNN optimized by genetic algorithm, is faster and offers smaller prediction error on the springback due to local bending.

Using records, documents, and research on Jiujing Sanshi Hall in Changchun Garden as an example, this paper showcases a method to digitally restore lost constructions to the maximum level of precision in their size, scale, architectural design, and structure using digital technology. The digital restoration can also be dynamically adjusted based on latest data. Information used to form such restorations include historical records, measurement data, and unknown data, which were then analyzed and recombined. This method fulfills the technical gap in high-precision digital restoration in China. The paper proposes an evaluation standard that involves "triple-evidence verification chain" and restoration accuracy, which can be used for most unmovable cultural relics, especially large ruins with few, scattered remains. The standard can provide a qualitative basis for the whole field of restoration research. The resulting restoration method is useful in cooperation and research between multiple cross-discipline organizations, as well as improving work efficiency and information sharing. Moreover, this restoration plan has integrated various virtual assembly methods and improved the integrity and authenticity of the site remains. It made breakthroughs in display methods of lost constructions and ruins such as enhanced showcasing of vanished ruins and changes over time. The plan also was able to enrich cultural connotation and existing contents of the ruins. The resulting restoration can be updated, and the information can be shared and used in open research.

Newborn poultry in cold regions often suffer from cold stress, causing a series of changes in their physiology and metabolism, leading to slow growth and decreased production performance. However, a single anti-stress substance cannot completely or maximally eliminate or alleviate the various effects of cold stress on animals. Therefore, the effects of the supplemented glutamine and L-carnitine on broilers under low temperature were evaluated in this study. Broilers were randomly allocated into 16 groups which were respectively fed with different levels of glutamine and L-carnitine according to the L16 (45) orthogonal experimental design for 3 weeks (the first week is the adaptive feeding period; the second and third weeks are the cold exposure period). Growth performance was recorded, and blood samples were collected during cold exposure. The results showed the supplementation had altered the plasma parameters, growth performance and cold-induced oxidative stress. The increase of corticosterone and suppression of thyroid hormone was ameliorated. Supplemented groups had lower daily feed intake and feed-to-gain ratio, higher daily weight gain and better relative weights of immune organs. Plasma glucose, total protein, blood urea nitrogen and alkaline phosphatase changed as well. Oxidative stress was mollified due to the improved activities of superoxide dismutase and glutathione peroxidase, heightened total antioxidant capacity and stable malondialdehyde. Dietary glutamine and L-carnitine improve the growth performance, nutritional status and cold stress response of broilers at low temperature, and their interaction occurred.

In recent years, hydraulic quadruped robots have received increasing attention because of their strong environment adaptability and high load capacity. However, weight control is an important issue for mobile systems in consideration of limited onboard energy. Overweight will cause extra load on joints, reduce the flexibility of movement, and consume more power. Topology optimization is an effective tool to reduce volume and weight while maintaining enough strength. This article takes both optimal geometries and contained flow channels into consideration and gives solutions to structure design and good print quality in a manifold used on a robot. Using topology optimization, the volume of the manifold is further reduced by 50.7 %, while it can meet the mechanical requirement for actual application.

The failure behavior and the corresponding physical mechanism of the AlGaN/GaN high electron mobility transistors (HEMTs) under transmission line pulse (TLP) stress were investigated in this paper. The result shows that the output and transfer characteristics of the AlGaN/GaN HEMTs after 90 cycles begin to degrade by comparing with the fresh ones under 40 V TLP voltage, and the gate leakage current of the devices slightly increases. When the TLP voltage of 52 V was applied, a catastrophic failure occurs for the AlGaN/GaN HEMTs. Furthermore, the failure of the AlGaN/GaN HEMTs was located, and the micro-morphology of the abnormal spot was observed. The result shows that the gate metal was damaged due to the large TLP stress. The failure mechanism may be mainly attributed to the Joule heat that causes the high lattice temperature of 1160 K as well as the electric field, and it is higher than the melting point of Au (1064 K) in the gate metal (Au/Ti/Mo). The results may be useful in the design and application of electrostatic discharge (ESD) for AlGaN/GaN HEMTs.

The ESD effects on the E-mode AlGaN/GaN high-electron mobility transistors (HEMTs) with p-GaN gate are investigated under repetitive TLP pulses. Firstly, the degradation and recovery of output, transfer characteristics, gate-leakage characteristics and low-frequency noises (LFN) are analyzed in detail before and after reverse electrostatic discharge (ESD) stress. The experimental results show that the electrical characteristics of the devices gradually degraded as the transmission line pulse (TLP) pules increased. Subsequently, the LFN measurements are performed over the frequency range of 1 Hz–10 KHz by increasing TLP pulses. Finally, the recovery tendency of DC (direct current) characteristics and trap density are studied and discussed after resting the device at room temperature for 1 to 3 months. These results physically confirm that the mechanism of the performance degradation and recovery of the devices could be attributed to the trapping and releasing processes of electrons in the p-GaN layer and AlGaN barrier layer of AlGaN/GaN HEMTs, which change the electric field distribution under the gate.

Quantized circular photogalvanic effect (CPGE) is predicted in chiral topological semimetals, but the experimental observation remains challenging. Here, Ni et al. observe a large topological longitudinal photocurrent in CoSi, which is much larger than the photocurrent in any other chiral crystals, indicating quantized CPGE within reach upon doping and increase of the hot-carrier lifetime.

Abstract Chiral topological semimetals are materials that break both inversion and mirror symmetries. They host interesting phenomena such as the quantized circular photogalvanic effect (CPGE) and the chiral magnetic effect. In this work, we report a comprehensive theoretical and experimental analysis of the linear and nonlinear optical responses of the chiral topological semimetal RhSi, which is known to host multifold fermions. We show that the characteristic features of the optical conductivity, which display two distinct quasi-linear regimes above and below 0.4 eV, can be linked to excitations of different kinds of multifold fermions. The characteristic features of the CPGE, which displays a sign change at 0.4 eV and a large non-quantized response peak of around 160 μA/V2 at 0.7 eV, are explained by assuming that the chemical potential crosses a flat hole band at the Brillouin zone center. Our theory predicts that, in order to observe a quantized CPGE in RhSi, it is necessary to increase the chemical potential as well as the quasiparticle lifetime. More broadly, our methodology, especially the development of the broadband terahertz emission spectroscopy, could be widely applied to study photogalvanic effects in noncentrosymmetric materials and in topological insulators in a contact-less way and accelerate the technological development of efficient infrared detectors based on topological semimetals.

The quality of the 3D model reconstructed using multi-view satellite image depends on the quality of the image. To evaluate the geometric quality of the satellite image, we proposed a method to evaluate the geometric distortion for satellite images and defined the deviation coefficient as a metric to evaluate the bending degree of a curve. After projecting a ground grid consisting of straight lines into the image space, the geometric distortion of the image can be evaluated quantitatively by calculating the deviation coefficients of the projection trajectories. Experiments have been carried out with three datasets obtained by JiLin-1, GaoFen-2, and WorldView-3 respectively. The results show that the proposed method can used to evaluate the geometric quality of satellite images effectively, and this evaluation method will be useful in image selecting in 3D reconstruction using multi-view satellite images.

In this paper, the degradation behavior of the electrical characteristics was investigated, and trap analysis based on low-frequency noise (LFN) was carried out for the commercial 1.2-kV/30-A silicon carbide (SiC) power MOSFETs under repetitive short-circuit (SC) stress. The experiment results show that the on-state resistance (Rdson) and threshold voltage (Vth) increase significantly. Meanwhile, the drain-source current (Ids) decreases obviously with the increase of the SC cycles. Furthermore, the gatesource leakage current (Igss) of the SiC power MOSFETs increase greatly and the blocking characteristics deteriorated after 1000 SC cycles. The positive shift was observed on the gate-capacitance versus gatevoltage (Cg-Vg) curve, which shows that the damage region could be in channel along the SiC/SiO2 interface after repetitive SC stress. In order to obtain the trap information, trap characterization was performed by using LFN method, and the LFN results show that the trap density increases with the SC cycles. The physical mechanism could be attributed to electrically active traps generated at SiC/SiO2 interface and oxide layer due to the peak ionization rate, the perpendicular electrical field and high temperature during SC stress. The study may be useful to provide reference for converters design and fault protection of SiC power MOSFETs.

Based on the Deform-3D finite element simulation software, the numerical analysis of prefabricated holes in the core of ultra-heavy plates is carried out in different rolling schemes. In this paper, the deformation of the hole in core under uniform temperature rolling (UTR) is compared by different gradient temperature rolling (GTR) processes. The results show that the GTR can improve the core deformation compared with the UTR. The increase of the number of water cooling can accelerate the welding of the core holes and the healing of the final gap, and multi-pass watercooled GTR should be used for ultra-heavy plate rolling.

Based on the software Visual-Environment, Finite element method (FEM) was performed on the dissimilar butt-joint between Q345 and 2Cr13 steel aiming at the welding residual stress. The main contents in the paper were different current intensity was applied to modeling the welding process of Q345/2Cr13 dissimilar steel and the law of residual stress field were discussed. Based on the result, different current intensities have little effect on the lateral residual stress, while the longitudinal residual stress and the initial and end of the weld have a great influence. The physical properties of the dissimilar plates lead to uneven distribution of residual stress, and the current intensity should be smaller.

Without a global dipole magnetic field, Mars has magnetic anomalies, i.e., crustal fields, in the southern hemisphere and interesting flexible magnetic fields in the magnetotail. The magnetic field topology is complex and flexible in the Martian magnetotail, especially over regions of strong crustal fields. However, the answer to how the magnetic field topology within crustal field regions transitions is elusive. Here we report the first case of interchange reconnection between open and closed crustal fields in the near-Mars magnetotail, using Mars Atmosphere and Volatile Evolution (MAVEN) observations. While MAVEN crossed from a region of closed crustal field to one of open crustal field, several characteristics of reconnection, such as the Hall magnetic field and plasma outflow, were observed. And plasmas are exchanged in the reconnection region. Our observations demonstrate that interchange reconnection can occur between open and closed crustal fields in the Martian near-magnetotail. Interchange reconnection occurring on the nightside changes the magnetic field topology within the crustal field regions and contributes to the escape of heavy ions.

Assisted by the Magnetospheric Multiscale mission capturing unprecedented high-resolution data in the terrestrial magnetotail, we apply a local streamline-topology classification methodology to investigate the categorization of the magnetic field topological structures at kinetic scales in the turbulent reconnection outflow. It is found that strong correlations exist between the straining and rotational part of the velocity gradient tensor as well as the magnetic field gradient tensor. Strong energy dissipation prefers to occur at regions with high magnetic stress or current density, which is contributed mainly by O-type topologies. These results indicate that the kinetic structures with O-type topology play a more important role in energy dissipation in turbulent reconnection outflow.

Utilizing the unprecedented high-resolution Magnetospheric Multiscale mission data from 2015 September to 2017 December, we perform a statistical study of electron vortexes in the turbulent terrestrial magnetosheath. On the whole, 506 electron vortex events are successfully selected. Electron vortexes can occur at four known types of magnetic structures, including 78, 42, 26, and 39 electron vortexes observed during the crossings of the current sheets, magnetic holes, magnetic peaks, and flux ropes, respectively. Except for the four types of structures, the rest of the electron vortexes are in the “Others” category, defined as unknown structures. The electron vortexes mainly occur in the subsolar region, with only a few in the flank region. The total occurrence rate of all electron vortexes is 4.86 hr ^–1 , with, on average, 3.65 events hr ^−1 in the X-Y plane and 3.26 events hr ^−1 in the X-Z plane. The durations of most of the electron vortexes concentrate within 0.5–1.5 s and are 1.09 s on average. The electron vortexes are ion-scale structures owing to the average scale of 2.05 ion gyroradius. In addition, the means, medians, and maxima of the energy dissipation J · E ′ in the electron vortexes are almost positive, implying that the electron vortex may be a potential coherent structure or channel for turbulent energy dissipation. All these results reveal the statistical characteristics of electron vortexes in the magnetosheath and improve our understanding of energy dissipation in astrophysical and space plasmas.

The dramatic changes in the magnetic field at the dipolarization front (DF) provide a suitable environment for electron acceleration, which usually can cause the flux enhancement of energetic electrons behind the front. However, it is unknown whether energetic electrons observed at the DF are energized locally, and which mechanism accelerates the electrons at the DF is unclear. Our study performs a direct quantitative analysis to reveal the acceleration process of energetic electrons at the DF using the high-time-resolution data from NASA's Magnetospheric Multiscale mission. The fluxes of energetic electrons at 90° are enhanced at the front. Under adiabatic conditions, our quantitative analysis indicates that these electrons at the front could be locally accelerated to over 100 keV by betatron acceleration. Eventually, the electron temperature anisotropy formed via the betatron mechanism could provide the free energy to excite whistler waves at the DF. Our quantitative study provides, for the first time, strong direct evidence for the local electron acceleration at the DF.

ABSTRACT The present study was conducted to investigate the effects of dietary fiber on growth performance, fat deposition, serum lipids, fat metabolism, and mRNA (messenger RNA) expression of lipoprotein lipase (LPL) in Jilin white and Carlos geese. Sixty Jilin white and sixty Carlos geese aged six-weeks and of similar health and weight (average weight 313.11g) were selected. Geese of each breed were randomly divided into two groups (n=30), and with each group containing three replicate subgroups of 10 geese. The diet was supplemented with 8% or 11% fiber (corn straw powder). The Jilin white geese are divided into A1 (8%) and A2 (11%) groups, and Carlos geese are divided into B1 (8%) and B2 (11%) groups. The experiment lasted 35 days. The results showed that high dietary fiber can significantly (p

Based on the numerical simulation software Visual-Environment, the numerical calculation and analysis of residual stress field under different preheating temperatures for Q345/2Cr13 dissimilar plate welding were carried out in this paper. The effects of different preheating temperatures on post-weld residual stress were mainly studied. The results showed that different preheating temperatures have little effect on the lateral residual stress, while the longitudinal residual stress and the initial and end of the weld have greater impacts. For residual stress difference between the two base metals should not be too high, the dissimilar plate welding should adopt a moderate preheating temperature.

Based on the welding numerical simulation software Visual-environment, this paper calculates and analyzes the residual stress field for the double pass welding of Q345 stacked plates. The paper mainly studies the influence of different welding directions on the residual stress after welding. The results show that different welding methods have little effect on the lateral residual stress, while the longitudinal residual stress and the initial and end of the weld have a greater influence, while the post-weld residual stress distribution of the anisotropic two-pass weld is more uniform.

With the completion of the Beijing Five-year Clean Air Action Plan by the end of 2017, the annual mean PM2.5 concentration in Beijing dropped dramatically to 58.0 µg m−3 in 2017 from 89.5 µg m−3 in 2013. However, controversies exist to argue that favourable meteorological conditions in 2017 were the major driver for such a rapid decrease in PM2.5 concentrations. To comprehensively evaluate this 5-year plan, we employed a Kolmogorov–Zurbenko (KZ) filter and WRF-CMAQ (Weather Research and Forecasting and the Community Multi-scale Air Quality) to quantify the relative contribution of meteorological conditions and the control of anthropogenic emissions to PM2.5 reduction in Beijing from 2013 to 2017. For these 5 years, the relative contribution of emission reduction to the decrease in PM2.5 concentrations calculated by KZ filtering and WRF-CMAQ was 80.6 % and 78.6 % respectively. KZ filtering suggested that short-term variations in meteorological and emission conditions contributed majorly to rapid changes in PM2.5 concentrations in Beijing. WRF-CMAQ revealed that the relative contribution of local and regional emission reduction to the PM2.5 decrease in Beijing was 53.7 % and 24.9 % respectively. For local emission-reduction measures, the regulation of coal boilers, increasing use of clean fuels for residential use and industrial restructuring contributed 20.1 %, 17.4 % and 10.8 % to PM2.5 reduction respectively. Both models suggested that the control of anthropogenic emissions accounted for around 80 % of the PM2.5 reduction in Beijing, indicating that emission reduction was crucial for air quality enhancement in Beijing from 2013 to 2017. Consequently, such a long-term air quality clean plan should be continued in the following years to further reduce PM2.5 concentrations in Beijing.

Abstract The Compact Linear Collider (CLIC) is a proposed future high-luminosity linear electron-positron collider operating at three energy stages, with nominal centre-of-mass energies s $$ \sqrt{s} $$ = 380 GeV, 1.5 TeV, and 3 TeV. Its aim is to explore the energy frontier, providing sensitivity to physics beyond the Standard Model (BSM) and precision measurements of Standard Model processes with an emphasis on Higgs boson and top-quark physics. The opportunities for top-quark physics at CLIC are discussed in this paper. The initial stage of operation focuses on top-quark pair production measurements, as well as the search for rare flavour-changing neutral current (FCNC) top-quark decays. It also includes a top-quark pair production threshold scan around 350 GeV which provides a precise measurement of the top-quark mass in a well-defined theoretical framework. At the higher-energy stages, studies are made of top-quark pairs produced in association with other particles. A study of t̄tH production including the extraction of the top Yukawa coupling is presented as well as a study of vector boson fusion (VBF) production, which gives direct access to high-energy electroweak interactions. Operation above 1 TeV leads to more highly collimated jet environments where dedicated methods are used to analyse the jet constituents. These techniques enable studies of the top-quark pair production, and hence the sensitivity to BSM physics, to be extended to higher energies. This paper also includes phenomenological interpretations that may be performed using the results from the extensive top-quark physics programme at CLIC.

3D building models are needed for urban planning and smart city. These models can be generated from stereo aerial images, satellite images or LiDAR point clouds. In this paper, we propose a geometric object-based building reconstruction method from satellite imagery derived point clouds. The goal is to achieve a geometrically correct, topologically consistent, and non-redundant 3D representation for buildings in urban areas. The paper first introduces our motivation, followed by a comprehensive review on related works. We then introduce the methodology and process developed in this paper. Primary results from the point clouds generated from WorldView high resolution satellite images are used to demonstrate the performance of the approach.

To comprehensively evaluate the effects of the recent “2+26” regional strategy for air quality improvement, we compared the variations in PM2.5 concentrations in Beijing during four pollution episodes with different emission-reduction strategies. The 2+26 strategy implemented in March 2018 led to a mean PM2.5 concentration 16.43 % lower than that during the pollution episode in March 2013, when no specific emission-reduction measures were in place. The same 2+26 strategy implemented in November 2017 led to a mean PM2.5 concentration 32.70 % lower than that during the pollution episode in November 2016, when local emission-reduction measures were implemented. The results suggested that the effects of the 2+26 regional emission-reduction measures on PM2.5 reductions were influenced by a diversity of factors and could differ significantly during specific pollution episodes. Furthermore, we found the proportions of sulfate ions decreased significantly, and nitrate ions were the dominant PM2.5 components during the two 2+26 orange alert periods. Meanwhile, the relative contribution of coal combustion to PM2.5 concentrations in Beijing during the pollution episodes in March 2013, November 2016, November 2017 and March 2018 was 40 %, 34 %, 28 % and 11 %, respectively, indicating that the recent “Coal to Gas” project and the contingent 2+26 strategy led to a dramatic decrease in coal combustion in the Beijing–Tianjin–Hebei region. On the other hand, the relative contribution of vehicle exhaust during the 2+26 orange alert periods in November 2017 and March 2018 reached 40 % and 54 %, respectively. The relative contribution of local emissions to PM2.5 concentrations in Beijing also varied significantly and ranged from 49.46 % to 89.35 % during the four pollution episodes. These results suggested that the 2+26 regional emission-reduction strategy should be implemented with red air pollution alerts during heavy pollution episodes to intentionally reduce the dominant contribution of vehicle exhausts to PM2.5 concentrations in Beijing, while specific emission-reduction measures should be implemented accordingly for different cities within the 2+26 framework.